Universal Data Modeling: A Unified Approach for Intelligent Data Models

By Jun Shan

Most data professionals work with multiple datasets scattered across teams, systems, and formats. But without a clear modeling strategy, the result is often chaos: mismatched schemas, fragile pipelines, and a constant fight to make sense of the noise. This essential guide offers a better way by introducing a practical framework for designing high-quality data models that work across platforms while supporting the growing demands of AI, analytics, and real-time systems.

Author Jun Shan bridges the gap between disconnected modeling approaches and the need for a unified, system-agnostic methodology. Whether you're building a new data platform or rethinking legacy infrastructure, Universal Data Modeling gives you the clarity, patterns, and tools to model data that's consistent, resilient, and ready to scale.

Connect conceptual, logical, and physical modeling phases with confidence Apply best-fit techniques across relational, semistructured, and NoSQL formats Improve data quality, clarity, and maintainability across your organization Support modern design paradigms like data mesh and data products Translate domain knowledge into models that empower teams Build flexible, scalable models that stand the test of technology change

• Format: Paperback
• Language: English
• ISBN: B0H7HLP3Z6
• ISBN13: 9798341665316
• Release Date: February 2027
• Publisher: O'Reilly Media
• Length: 350 Pages